Triple

T504429
Position Surface form Disambiguated ID Type / Status
Subject Tunes E10470 entity
Predicate locatedInMetropolitanRegion P294 FINISHED
Object Algarve metropolitan area E6079 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Algarve metropolitan area | Statement: [Tunes, locatedInMetropolitanRegion, Algarve metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algarve metropolitan area
Context triple: [Tunes, locatedInMetropolitanRegion, Algarve metropolitan area]
  • A. Algarve chosen
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
  • B. Alentejo
    Alentejo is a large, sparsely populated region in southern Portugal known for its rolling plains, cork oak forests, vineyards, and historic whitewashed towns.
  • C. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • D. Coimbra
    Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
  • E. Lisbon
    Lisbon is the coastal capital city of Portugal, renowned for its historic architecture, hilly landscape, and role as a major cultural and economic center in Europe.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a2e848adf881908e5e04f7af030093 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f149bd1c81908ff58ac504ace2bf completed Feb. 28, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4cc5868d88190bb0b107fb820aafe completed March 1, 2026, 11:31 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.